Title :
Research on self-similarity network group
Author :
Xuan, Yaguang ; Tao, Shaohua
Author_Institution :
Network Manage. Center, Xuchang Univ., Xuchang, China
Abstract :
The paper aims to clearify some of the self-similar nature of network group, which based on the fact that current research on network group tends to neglect its wide range of self-similarity. First, the Toeplitz matrices is introduced, because a self-similar network has the characteristics of obvious upper triangular or lower triangular Toeplitz matrix, which generalizes that the self-similar network group has exchangeable, reversibility and symmetry. We also studied the intersection and union set of self-similar local area network, then proposed that a self-similar network group is able to transfer of information faster. Simulation results show that self-similar network can transfer information much faster than BA network, which proves the correctness of the theory.
Keywords :
Toeplitz matrices; local area networks; set theory; BA network; Toeplitz matrices; information transfer; intersection set; lower triangular Toeplitz matrix; self-similar local area network; self-similarity network group; union set; upper triangular Toeplitz matrix; Artificial neural networks; Barium; Complex networks; Manganese; Nickel; Social network services; Tin; complex network; self-similarity network group; self-similartiy; toeplitz matrix;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-8727-1
DOI :
10.1109/CSAE.2011.5952632